The classification of lung cancer using deep learning Techniques
Last updated: 09 Mar 2025
10.21608/aels.2024.270817.1047
Keywords: Convolutional Neural Networks (CNN), Medical Imaging, early diagnosis, Class Imbalance, Synthetic Minority Over-sampling Technique (SMOTE)
Ola
Khedr
Salah
Department of Mathematics - Computer Sciences, Faculty of Science, Suez Canal University, Ismailia, 41552, Egypt
ola_salah@science.suez.edu.eg
Mohamed
Wahed
Department of Computer Sciences, Faculty of Computers and Informatics, Suez Canal University, Ismailia, 41552, Egypt
drmoh@ci.suez.edu.eg
Al-Sayed
Al-Attar
Department of Pathology, Faculty of Veterinary medicine, Zagazig University, Zagazig, 11144, Egypt
arabdelmegeed@vet.zu.edu.eg
Entsar
Abdel-Rehim
Ahmed
Department of Mathematics - Computer Sciences, Faculty of Science, Suez Canal University, Ismailia, 41552, Egypt
entsar_abdalla@science.suez.edu.eg
5
2
54223
2024-03-01
2024-02-17
2024-03-01
21
33
2805-3060
2805-3079
https://aels.journals.ekb.eg/article_344249.html
http://journals.ekb.eg?_action=service&article_code=344249
2
Original research articles
2,116
Journal
Advances in Environmental and Life Sciences
https://aels.journals.ekb.eg/
The classification of lung cancer using deep learning Techniques
Details
Type
Article
Created At
09 Mar 2025